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题目链接:https://leetcode.com/problems/increasing-triplet-subsequence/
题目:
Given an unsorted array return whether an increasing subsequence of length 3 exists or not in the array.
Formally the function should:
Return true if there exists i, j, k
such that arr[i] < arr[j] < arr[k] given 0 ≤ i < j < k ≤ n-1 else return false.
Your algorithm should run in O(n) time complexity and O(1) space complexity.
Examples:
Given [1, 2, 3, 4, 5]
,
return true
.
Given [5, 4, 3, 2, 1]
,
return false
.
思路:
1、c[i] = max{c[j]+1,1} j<i 且nums[i]>nums[j]
时间复杂度O(n^2),空间复杂度O(n)
2、
利用二分搜索,这里二分搜索的空间是常数项,所耗费的时间、空间都可以看成O(1)复杂度
算法1:
public boolean increasingTriplet(int[] nums) { if (nums.length < 3) return false; int c[] = new int[nums.length];// c[i]表示从0~i 以nums[i]结尾的最长增长子串的长度 c[0] = 1; for (int i = 1; i < nums.length; i++) { int tmp = 1; for (int j = 0; j < i; j++) { if (nums[i] > nums[j]) { tmp = Math.max(c[j] + 1, tmp); } } c[i] = tmp; if (c[i] >= 3) return true; } return false; }
算法2:
public boolean increasingTriplet(int[] nums) { if (nums.length < 3) return false; int b[] = new int[3+1];// 长度为i的子串 最后一个数最小值 int end = 1; b[end] = nums[0]; for (int i = 1; i < nums.length; i++) { if (nums[i] > b[end]) {// 比最长子串最后元素还大,则更新最长子串长度 end++; b[end] = nums[i]; if(end>=3) return true; } else {// 否则更新b数组 int idx = binarySearch(b, nums[i], end); b[idx] = nums[i]; } } return false; } /** * 二分查找大于t的最小值,并返回其位置 */ public int binarySearch(int[] b, int target, int end) { int low = 1, high = end; while (low <= high) { int mid = (low + high) / 2; if (target > b[mid]) low = mid + 1; else high = mid - 1; } return low; }
算法2:
【Leetcode】Increasing Triplet Subsequence
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原文地址:http://blog.csdn.net/yeqiuzs/article/details/51520489